Aimed at investment professionals or those with investment industry knowledge, this course offers an introduction to the basic data and statistical techniques that underpin data analysis and lays an essential foundation in the techniques that are used in big data and machine learning. It introduces the topics and gives practical examples of how they are used by investment professionals, including the importance of presenting the “data story" by using appropriate visualizations and report writing.
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In this course you will learn how to:
- Explain basic statistical measures and their application to real-life data sets
- Calculate and interpret measures of dispersion and explain deviations from a normal distribution
- Understand the use and appropriateness of different distributions
- Compare and contrast ways of visualizing data and create them using Python (no prior knowledge of Python necessary)
- Explain sampling theory and draw inferences about population parameters from sample statistics
- Formulate hypotheses on investment problems
Course 1 of 3 in the Data Science for Investment Professionals Specialization.
What You Will Learn
- Demonstrate the importance of and techniques for presenting data and the “data story”
- Understand data distributions and the importance and use of statistical measures
- Use statistical sampling and hypothesis testing to gain insight into population parameters
- Calculate data statistics and produce visualizations using Python
Syllabus
WEEK 1
Welcome to Data and Statistics Foundation for Investment Professionals
Measures of Central Tendency
WEEK 2
Measures of Dispersion
WEEK 3
Distributions
WEEK 4
Data Visualization Techniques
WEEK 5
Sampling Theory
WEEK 6
Hypothesis Testing
WEEK 7
Final Project
The final project places you in the role of a junior analyst who has been presented with data and needs to manipulate it in a meaningful way and present your findings to your manager in a well written report. It will test many of the things, including Python, that you have learned throughout this course. This final assessment is worth a maximum of 40% (out of a total of 100%) and counts towards your success in this course.
